Video frame interpolation (VFI) is a classical low-level vision task to increase the frame rate of a video sequence.
The recent years have witnessed the rapid development of VFI empowered by the success of deep neural networks [1]}, [2]}, [3]}. However, it remains some unsolved problems due to challenges like occlusions, large motion, and lighting changes.
According to whether or not the optical flow information is incorporated, the existing VFI approaches can be roughly divided into two categories: 1) motion-based methods and 2) motion-free methods.
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